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\title{Disease Mapping Assignment}
\author{Patrick Brown}
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\maketitle

For this project you will be given a real dataset and a collaborating epidemiolgist (either Dionne Gesink Law or Susitha Wanigaratne).  Address your question by producing a report which will be read and graded by an epidemiologist as well as me.  Include sections in your report similar to the following

\begin{itemize}
	\item Introduction: describe the problem and the data, and present some simple exploratory analysis.  
	\item Methods: describe and justify your model and method of inference. Explain how the problem relates to a statistical hypothesis.
	\item Results: show results, with a handful of maps and tables with proper captions and described in the text of your document.
	\item Discussion: Relate the results to the problem presented.  Discuss the limitations of your analysis: is the ecological fallacy a problem?
\end{itemize}

This coursework will form 60\% of the final grade, and will be due sometime in mid-december.

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\section{Billy Chang -- Smoking in Hamilton}
Using the Canadian Community Househod Survey data, make a map of smoking incidence in Hamilton by census subdivision (CSD).  Produce a map of estimated incidence and a map of the probabilities of each CSD having above average smoking rates.  Do this for the rate of current smokers and of former smokers, as a proportion of the population.  Make sure to use income as a covariate.

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\section{Benny Wong-- tuberculosis in southern USA}

Using data provided by Dionne Gesink Law, produce maps of the risk of your respective disease at the county level, and assess the contribution to risk of income and other important covariates provided.  Fit income as a non-linear effect, at a minimum make it linear with a change point at the average income level.  

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\section{Ashley Liao -- Ghonerea in southern USA}

Using data provided by Dionne Gesink Law, produce maps of the risk of your respective disease at the county level, and assess the contribution to risk of income and other important covariates provided.  Fit income as a non-linear effect, at a minimum make it linear with a change point at the average income level.  


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\section{Chris Meaney -- screening for colorectal cancer}

The two methods of screening for colorectal cancer (FOBT and colonoscopy) have striking spatial patterns in incidence rates in Toronto.  It is hypothesised that wealthier individuals are more likely to choose a colonoscopy over FOBT.  Assess this hypothsis by using a spatial model at the Census Tract level.

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\section{Lung Cancer in Toronto -- Andrew Calzavara}
The Jane-Finch community is a distinctive community in Toronto, and it is hypothesised that lung cancer risk there is high there as a result of the community's characteristics.   Modelling lung cancer incidence at the census tract level, assess the hypothesis.  If there is higher risk in the area, can it be explained by the low income levels?

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\section{Pollution in Hamilton -- Kai He}

It is hypothesised that steel and iron foundries in Hamilton producing pollution which is causing lung cancer.  Assess this hypothesis in two ways.  First, use distance from the foundries as a proxy for pollution, and test whether risk is higher within 2km of the plants than in areas further away. Second, use estimated pollution levels as a covariate in the model.  


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